Multi-threshold image segmentation based on three-dimensional Tsallis entropy

Image multi-threshold segmentation method based on three-dimensional Tsallis entropy is proposed by utilizing the non-extensive property of Tsallis entropy in the paper. The improved particle swarm optimization (PSO) is used to search best two-dimensional multi-threshold vector by maximising the three-dimensional Tsallis entropy. The proposed method not only considers the gray distribution information of pixels and relevant information of neighbouring pixels, but also the interaction between the object and the background, the different responses in variant grey level. The experimental results show that the new algorithm is better than the tradition methods with both a better stability.